Pour Water Between Buckets to Make Water Levels Equal
A medium-tier problem at 67% community acceptance, tagged with Array, Binary Search. Reported in interviews at Deutsche Bank and 0 others.
You're given buckets with different water levels, and you need to pour water between them until levels are equal. Deutsche Bank asks this one, and it shows up occasionally across other finance and tech screens. The problem looks straightforward at first: just simulate pouring. But the real trick is recognizing that you can't always make all buckets equal, and the naive greedy approach will time out on large inputs. This is where binary search saves you. The acceptance rate sits at 67%, which means roughly one in three candidates either times out or misses the pattern entirely. If this lands in your assessment and you blank on the binary search angle, StealthCoder runs invisibly during your screen share and surfaces the working solution in seconds.
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Pour Water Between Buckets to Make Water Levels Equal is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Built by a senior engineer who knows the OA is theater. This is the script.
Get StealthCoderThe gotcha here is that you can't necessarily equalize all buckets in one pass. Some buckets may not participate in the final level. The key insight is to binary search on the final water level itself, not on the number of operations. For each candidate level, you check if it's achievable by simulating the pouring process: each bucket either contributes excess or receives shortage. If total water is sufficient and the simulation confirms feasibility, that level works. The common pitfall is trying to greedily pour bucket by bucket, which either gets stuck or explodes in complexity. Binary search sidesteps that entirely. You're not searching through states or iterations, you're searching through possible outcome values. This is a clean application of the "binary search on the answer" pattern, and it's exactly the kind of misdirection that trips up candidates who only drill greedy simulations. Even if you haven't seen this pattern before, StealthCoder will show you the framework instantly when you need it most.
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Pour Water Between Buckets to Make Water Levels Equal recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Built by a senior engineer who knows the OA is theater. This is the script. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Pour Water Between Buckets to Make Water Levels Equal interview FAQ
Do all buckets have to end up at the same level?+
Not necessarily. Some buckets may not participate in the final equalization. You're looking for the maximum level that the majority (or a valid subset) can reach simultaneously, given total water constraints. Binary search on this maximum level, then verify it's achievable.
Why does greedy pouring fail here?+
Greedy approaches assume you process buckets in a fixed order and always pour to the next bucket. This misses the global constraint: total water divided by number of buckets gives a hard ceiling. Greedy can overshoot or get stuck in cycles, making it slow or incorrect.
How does binary search fit the Array and Binary Search topics?+
You iterate over bucket values (the array), but the actual search space is numeric: the range from the minimum current level to the average. Binary search that numeric range and validate each candidate level by simulating the pour.
Is this problem still asked at Deutsche Bank and similar firms?+
It appears in occasional finance tech interviews, particularly for roles involving systems design or algorithmic optimization. The 67% acceptance rate suggests it's not a gimmick problem, but the binary search twist catches unprepared candidates.
What's the time complexity after using binary search?+
Binary search runs in O(log W) iterations, where W is the max water level. Each iteration simulates pouring across all buckets in O(n). Total is O(n log W), which beats naive simulation and is acceptable for most online assessments.
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